The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

Steen, Chloé B.; Luca, Bogdan A.; Esfahani, Mohammad Shahrokh; Azizi, Armon; Sworder, Brian; Nabet, Barzin Y.; Kurtz, David M.; Liu, Chih Long; Khameneh, Farnaz; Advani, Ranjana H.; Natkunam, Yasodha; Myklebust, June Helen; Diehn, Maximilian; Gentles, Andrew J.; Newman, Aaron M.; Alizadeh, Ash A.

doi:10.1016/j.ccell.2021.08.011

Cited by 136 publications

(126 citation statements)

References 96 publications

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“…Next, we investigated the role of PD-1 and A2aR in the phenotype of dysfunctional CD8 + T cells at the single-cell RNA expression level using the publicly available dataset GSE182434. 20 CD8 + T cells had been annotated in four DLBCL samples. We further classified CD8 + T cells into seven clusters by Seurat ( figure 5A ).…”

Section: Resultsmentioning

confidence: 99%

“…The processed dataset (GSE182434) of publicly available data for single-cell RNA sequencing was downloaded from the NCBI GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ). 20 CD8 + T cells had been annotated in four DLBCL samples. We then used Seurat v3.1.2 21 to normalize and scale the expression matrices by function NormalizeData and ScaleData.…”

Section: Methodsmentioning

confidence: 99%

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Genetic characteristics involving the PD-1/PD-L1/L2 and CD73/A2aR axes and the immunosuppressive microenvironment in DLBCL

Zhang

Liu

Jiao³

et al. 2022

J Immunother Cancer

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BackgroundTargeting the PD-1/PD-L1/L2 (programmed cell death protein 1/programmed cell death ligand 1/ligand 2) pathway combined with other immunosuppressive signalings, such as CD73/A2aR (A2a adenosine receptor) adenosine signaling, has emerged as a promising strategy for cancer treatment. The genetic characteristics of these immune checkpoints need to be further investigated in diffuse large B-cell lymphoma (DLBCL).MethodsWe performed whole-exome sequencing/targeted deep sequencing to investigate the genetic characteristics of PD-1/PD-L1/L2 and CD73/A2aR. The immunosuppressive effect of these two pathways on the tumor microenvironment was evaluated via RNA sequencing. Single-cell RNA sequencing was further applied to investigate the dysfunctional CD8+ T cells. In addition, multiplex immunofluorescence staining was used to quantitatively assess the expression of dysfunctional CD8+ T cells in DLBCL.ResultsSP140 was identified as a novel translocation partner for PD-L1, and a new inversion was detected between PD-L1 and PD-L2, both leading to the upregulation of PD-L1 expression. CD73 genetic mutations did not increase mRNA and protein expression. Patients with genetically altered CD73 tended to have a better overall survival than patients with wild-type CD73. Both PD-1/PD-L1 and CD73/A2aR signaling mediated the immunosuppressive microenvironment in DLBCL. The numbers of CD8+ T cells with PD-1 and A2aR expression were positively correlated with the number of dysfunctional CD8+ T cells (R2=0.974, p=0.013). According to the grades of dysfunctional CD8+ T cells we defined, grade 1 dysfunctional CD8+ T cells, with either PD-1+ or A2aR+, were significantly associated with poorer survival than grade 0 dysfunctional CD8+ T cells, with both PD-1− and A2aR−; and patients with grade 2 dysfunctional CD8+ T cells showed the worst clinical outcomes.ConclusionsThis study describes the additional genetic basis of PD-L1 overexpression and characterizes certain genetic alterations of CD73/A2aR in DLBCL. The degree of T-cell dysfunction is correlated with clinical outcomes. Strategies that reverse T-cell dysfunction by inhibiting PD-1/PD-L1/L2, particularly in combination with CD73/A2aR, may show potential as effective therapeutic options for DLBCL.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genetic characteristics involving the PD-1/PD-L1/L2 and CD73/A2aR axes and the immunosuppressive microenvironment in DLBCL

Zhang

Liu

Jiao³

et al. 2022

J Immunother Cancer

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“…In addition, a study using microarray-based GEP in 23 PCNSL cases demonstrated overlapping expression of germinal-center and activated B-cell genes [37]. In line with these findings, recent studies in DLBCL-NOS also demonstrated that binary classification into ABC or GCB does not correspond to the more complex biology as identified by transcriptomics and that recurrent genetic alterations are identified beyond the established COO subtypes [38][39][40].…”

Section: Discussionmentioning

confidence: 78%

“…Nevertheless, the poor correspondence and high percentage (43%) of UI may suggest a different biology of PCDLBCL-LT compared with DLBCL-NOS for which these algorithms were originally developed. Future studies need to investigate this observation with more comprehensive transcriptomic analysis, such as the EcoTyper, as recently described by Steen et al [40].…”

Section: Discussionmentioning

confidence: 96%

Cell-of-origin classification using the Hans and Lymph2Cx algorithms in primary cutaneous large B-cell lymphomas

et al. 2022

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Primary cutaneous diffuse large B-cell lymphoma, leg type (PCDLBCL-LT) and primary cutaneous follicle center lymphoma with a diffuse population of large cells (PCFCL-LC) are both primary cutaneous B-cell lymphomas with large-cell morphology (CLBCL) but with different clinical characteristics and behavior. In systemic diffuse large B-cell lymphoma, not otherwise specified (DLBCL-NOS), gene-expression profiling (GEP) revealed two molecular subgroups based on their cell-of-origin (COO) with prognostic significance: the germinal center B-cell-like (GCB) subtype and the activated B-cell-like (ABC) subtype. This study investigated whether COO classification is a useful tool for classification of CLBCL. For this retrospective study, 51 patients with PCDLBCL-LT and 15 patients with PCFCL-LC were analyzed for their COO according to the immunohistochemistry-based Hans algorithm and the NanoString GEP-based Lymph2Cx algorithm. In PCFCL-LC, all cases (100%) classified as GCB by both Hans and Lymph2Cx. In contrast, COO classification in PCDLBCL-LT was heterogeneous. Using Hans, 75% of the PCDLBCL-LT patients classified as non-GCB and 25% as GCB, while Lymph2Cx classified only 18% as ABC, 43% as unclassified/intermediate, and 39% as GCB. These COO subgroups did not differ in the expression of BCL2 and IgM, mutations in MYD88 and/or CD79B, loss of CDKN2A, or survival. In conclusion, PCFCL-LC uniformly classified as GCB, while PCDLBCL-LT classified along the COO spectrum of DLBCL-NOS using the Hans and Lymph2Cx algorithms. In contrast to DLBCL-NOS, the clinical relevance of COO classification in CLBCL using these algorithms has limitations and cannot be used as an alternative for the current multiparameter approach in differentiation of PCDLBCL-LT and PCFCL-LC.

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“…IN-LME is enriched in CD8 + T cells and a subpopulation of CD8 + T cells with high PD-1 expression and high expression of the immune checkpoint molecule PD-L1 and the tryptophanolytic enzyme IDO1, suggesting that this LME class may benefit from ICIs treatment. Steen CB et al characterized clinically relevant DLBCL cell states and ecosystems with EcoTyper (a machine-learning framework integrating transcriptome deconvolution and single-cell RNA sequencing), identified 5 cell states of malignant B cells with different prognostic associations and differentiation status, and revealed nine multicellular ecosystems in DLBCL, known as lymphoma ecotypes (LE) ( Steen et al, 2021 ). They found T-cell transcriptomic heterogeneity in DLBCL and that tumors high in LE4 are characterized by an immunoreactive T-cell state with widespread expression of co-inhibitory and stimulatory molecules, with potential implications for immunotherapeutic targeting.…”

Section: Discussionmentioning

confidence: 99%

Single-Cell RNA-Seq and Bulk RNA-Seq Reveal Intratumoral Heterogeneity and Tumor Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma

Zhao

Zhang

et al. 2022

Front. Genet.

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Background: Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin’s lymphoma (NHL) with highly heterogeneous genetic and phenotypic features. Therefore, a comprehensive understanding of cellular diversity and intratumoral heterogeneity is essential to elucidate the mechanisms driving DLBCL progression and to develop new therapeutic approaches.Methods: We analyzed single-cell transcriptomic data from 2 reactive lymph node tissue samples and 2 DLBCL lymph node biopsy tissue samples to explore the transcriptomic landscape of DLBCL. In addition, we constructed a prognostic model based on the genes obtained from differential analysis.Results: Based on gene expression profiles at the single cell level, we identified and characterized different subpopulations of malignant and immune cells. Malignant cells exhibited a high degree of inter-tumor heterogeneity. Tumor-infiltrating regulatory CD4+ T cells showed highly immunosuppressive properties and exhausted cytotoxic CD8+ T cells were highly expressed with markers of exhaustion. Cell communication analysis identified complex interactions between malignant cells and other cell subpopulations. In addition, the prognostic model we constructed allows for monitoring the prognosis of DLBCL patients.Conclusion: This study provides an in-depth dissection of the transcriptional features of malignant B cells and tumor microenvironment (TME) in DLBCL and provides new insights into the tumor heterogeneity of DLBCL.

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The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

Cited by 136 publications

References 96 publications

Genetic characteristics involving the PD-1/PD-L1/L2 and CD73/A2aR axes and the immunosuppressive microenvironment in DLBCL

Genetic characteristics involving the PD-1/PD-L1/L2 and CD73/A2aR axes and the immunosuppressive microenvironment in DLBCL

Cell-of-origin classification using the Hans and Lymph2Cx algorithms in primary cutaneous large B-cell lymphomas

Single-Cell RNA-Seq and Bulk RNA-Seq Reveal Intratumoral Heterogeneity and Tumor Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma

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